Digitization of documents, such as historical documents, provides on-line customers with ready access to those documents. Digitizing the images typically involves: scanning documents, whether they be from paper, books, microfilm, and/or the like; performing image processing on the documents to improve them in some way or ways; checking the images for quality problems (i.e., quality assurance, or QA); rescanning the images if quality is insufficient; and/or the like.
Often images are indexed in some way (e.g., manually by keying operators or using optical Character recognition (OCR)) to provide search or browse mechanisms for users to find the appropriate images.
An image may be rejected for poor quality by a QA operator, by a keying operator, by an OCR engine, or even by a customer. The later in the pipeline that an image rescan is requested, the costlier the rescan is generally, because of all the work that has already been put into that image that now must be redone. Source documents may be difficult or even impossible to obtain again, making initial image quality more important. Hence, improved scanning systems and methods are needed.